Interference-Controlled Load Sharing with Femtocell Relay for Macrocells in Cellular Networks
Bibliographic record
Abstract
With the ever-growing demands of wireless communications, traffic load sharing is essentially important to provide consistent high quality of service (QoS). It is known that the QoS of mobile users is affected by the limited bandwidth in both wireless link and wired backhaul link beyond a base station (BS). Femtocell is a promising technology to bear part of the traffic load from the BS. Nonetheless, due to the small coverage and possible closed service policy, the number of users within a femtocell is so restricted that only a small part of the traffic load can be transferred via the femtocell. Hence, it has little help to relieve the regular BS traffic load. In this paper, we propose a femtocell relay method to increase the number of users using femtocell and further reduce the traffic load in macrocell. Specifically, femtocell users provide relay service for nearby users connected to the macrocell BS and get reward bonus through balancing the traffic load. The simulation results have shown that our method can effectively reduce the traffic load in the macrocell and improve the delivery performance for regular network traffic.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".